Along an assembly line, diapers and various types of other absorbent articles may be assembled by adding components to and otherwise modifying an advancing, continuous web of material. For example, in some processes, advancing webs of material are combined with other advancing webs of material. In other examples, individual components created from advancing webs of material are combined with advancing webs of material, which in turn, are then combined with other advancing webs of material. Webs of material and component parts used to manufacture diapers may include: backsheets, topsheets, absorbent cores, front and/or back ears, fastener components, and various types of elastic webs and components such as leg elastics, barrier leg cuff elastics, and waist elastics. Once the desired component parts are assembled, the advancing web(s) and component parts are subjected to a final knife cut to separate the web(s) into discrete diapers or other absorbent articles. The discrete diapers or absorbent articles may also then be folded and packaged.
For quality control purposes, absorbent article converting lines may utilize various types of sensor technology to inspect the webs and discrete components added to the webs along the converting line as absorbent articles are constructed. Example sensor technology may include vision systems, photoelectric sensors, proximity sensors, laser or sonic distance detectors, and the like. Product inspection data from the sensors may be communicated to a controller in various ways. In turn, the controller may be programmed to receive product inspection data, and in turn, make adjustments to the manufacturing process. In some instances, the controller may reject defective absorbent articles based on the product inspection data after the final knife cut at the end of the converting line.
As such, the controller may be programmed with various algorithms adapted to analyze the inspection data and provide desired control functions to the manufacturing process. The complexity and sophistication of the algorithms may vary with the type of inspection data being analyzed. In some configurations, a vision system may be configured to communicate image data from an inspection zone to a controller, wherein aspects of the image data may be analyzed by an algorithm to determine whether control actions should be executed. For example, the image data may be analyzed to determine whether a component is missing or improperly positioned during the assembly process. Depending upon whether other features, such as graphics, bond patterns, or wrinkles, also may be located in the inspection zone, the algorithm may need to be relatively more complex to enable the algorithm to distinguish the component or lack thereof from such other features in the inspection zone.
However, limitations of human generated inspection algorithms currently constrain the speed of algorithm development and the scope of what can be inspected. Consequently, it would be beneficial to generate and utilize algorithms capable of inspections that otherwise cannot be coded by humans to conduct relatively more sophisticated in-process inspection operations of assembled absorbent articles.